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      The oldest case of paedomorphosis in rove beetles and description of a new genus of Paederinae from Cretaceous amber (Coleoptera: Staphylinidae)

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          Abstract

          The ecology of extinct species from the Cretaceous is largely unknown. Morphological features of specimens preserved in amber can help to reveal habitats and evolutionary strategies that occurred in fossil lineages. An unusually small rove beetle (Staphylinidae) from the subfamily Paederinae with a Y-shaped suture on the head and modified tarsi and antennae is newly described here as Midinudon juvenis Tokareva & Żyła gen. et sp. nov. We hypothesise that such a combination of characters represents the earliest example of paedomorphosis in Staphylinidae and discuss other possible reasons that could explain the small size and morphological modifications of the new species. We provide the results of total-evidence phylogenetic analysis and discuss the relationships of Midinudon juvenis Tokareva & Żyła gen. et sp. nov. within Paederinae.

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          MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

          Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d N /d S rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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            IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era

            Abstract IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.
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              MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform.

              K Katoh (2002)
              A multiple sequence alignment program, MAFFT, has been developed. The CPU time is drastically reduced as compared with existing methods. MAFFT includes two novel techniques. (i) Homo logous regions are rapidly identified by the fast Fourier transform (FFT), in which an amino acid sequence is converted to a sequence composed of volume and polarity values of each amino acid residue. (ii) We propose a simplified scoring system that performs well for reducing CPU time and increasing the accuracy of alignments even for sequences having large insertions or extensions as well as distantly related sequences of similar length. Two different heuristics, the progressive method (FFT-NS-2) and the iterative refinement method (FFT-NS-i), are implemented in MAFFT. The performances of FFT-NS-2 and FFT-NS-i were compared with other methods by computer simulations and benchmark tests; the CPU time of FFT-NS-2 is drastically reduced as compared with CLUSTALW with comparable accuracy. FFT-NS-i is over 100 times faster than T-COFFEE, when the number of input sequences exceeds 60, without sacrificing the accuracy.
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                Author and article information

                Contributors
                atokareva@miiz.waw.pl
                D.Zyla@leibniz-lib.de
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                31 March 2023
                31 March 2023
                2023
                : 13
                : 5317
                Affiliations
                [1 ]GRID grid.413454.3, ISNI 0000 0001 1958 0162, Museum and Institute of Zoology, , Polish Academy of Sciences, ; Wilcza 64, 00-679 Warsaw, Poland
                [2 ]GRID grid.5254.6, ISNI 0000 0001 0674 042X, Natural History Museum of Denmark, ; Universitetsparken 15, 2100 Copenhagen, Denmark
                [3 ]GRID grid.39158.36, ISNI 0000 0001 2173 7691, The Hokkaido University Museum, Hokkaido University, ; Kita 10, Nishi 8, Kita-Ku, Sapporo, Hokkaido 060-0810 Japan
                [4 ]GRID grid.517093.9, ISNI 0000 0005 0294 9006, Leibniz Institute for the Analysis of Biodiversity Change, ; Martin-Luther-King-Platz 3, 20146 Hamburg, Germany
                Article
                32446
                10.1038/s41598-023-32446-2
                10066364
                37002406
                17616322-ed86-408a-8489-6d836550a50a
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 26 October 2022
                : 28 March 2023
                Funding
                Funded by: Polish National Science Centre
                Award ID: 2019/35/B/NZ8/03431
                Award ID: 2019/35/B/NZ8/03431
                Award ID: 2019/35/B/NZ8/03431
                Award Recipient :
                Funded by: Marie Sklodowska-Curie grant
                Award ID: 101018841 16
                Award Recipient :
                Funded by: Grant-in-Aid for JSPS Fellows
                Award ID: 20J00159
                Award Recipient :
                Funded by: Integrating Activities Programme BE-TAF
                Award ID: BETAF_C3_ZYLA
                Award Recipient :
                Funded by: Integrating Activities Programme
                Award ID: AT-TAF-2867, 823827
                Award Recipient :
                Funded by: Stiftung Leibniz-Institut zur Analyse des Biodiversitätswandels (LIB) (3515)
                Categories
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                Custom metadata
                © The Author(s) 2023

                Uncategorized
                computational biology and bioinformatics,evolution,genetics,zoology
                Uncategorized
                computational biology and bioinformatics, evolution, genetics, zoology

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